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Proceedings of

3rd International Conference on Advances In Civil, Structural and Environmental Engineering ACSEE 2015

"RUNOFF PREDICTION UNDER CLIMATE CHANGE: ARTIFICIAL NEURAL NETWORK APPROACH"

OMID BOZORG-HADDAD PARISA SARZAEIM
DOI
10.15224/978-1-63248-065-1-45
Pages
67 - 70
Authors
2
ISBN
978-1-63248-065-1

Abstract: “Nowadays climate change phenomena is identified as an environmental issue all over the world. In result of human industrial activities, measurements of green house gases are increased which leads to global warming and its sequences. In the last decades, concerns about average temperature rising and its potential destructive results were noted. Also water resources which is one of the most effective in human life, are not in security. So to efficient management, it is worthy to calculate the climate change impacts on important parameters in water resources such as runoff. But rainfallrunoff models are complex and in other hand data mining models had impressive progress in recent years and are helpful to predict runoff. Genetic programming (GP), artificial neural network (ANN) and support vector machine (SVM) are such data mining tools that have many uses in various fields. In the present paper, climate precipitation and temperature are estimated by HadCM3 AOGCM and statistic downscaling”

Keywords: climate change, runoff prediction, artificial neural network

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